Results 41 to 50 of about 900 (183)
On a new semilocal convergence analysis for the Jarratt method [PDF]
Journal of Inequalities and Applications, 2013 AbstractWe develop a new semilocal convergence analysis for the Jarratt method. Through our new idea of recurrent functions, we develop new sufficient convergence conditions and tighter error bounds. Numerical examples are also provided in this study.MSC:65H10, 65G99, 65J15, 47H17, 49M15.
Argyros, Ioannis K +2 more
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Convergence Behavior for Newton-Steffensen’s Method under -Condition of Second Derivative
Abstract and Applied Analysis, 2013 The present paper is concerned with the semilocal as well as the local convergence problems of Newton-Steffensen’s method to solve nonlinear operator equations in Banach spaces.
Yonghui Ling, Xiubin Xu, Shaohua Yu
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AlgorithmsIn the present paper, we prove a new local convergence theorem with initial conditions and error estimates that ensure the Q-quadratic convergence of a modification of the famous Weierstrass method.
Plamena I. Marcheva +2 more
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Two-point method for solving nonlinear equation with nondifferentiable operator (in Ukrainian) [PDF]
Математичні Студії, 2011 In the paper we study a combined differential-difference method for solving nonlinear equations with non-differentiable operator. The semilocal convergence of the method is investigated and the order of convergence is established.
S. M. Shakhno, H. P. Yarmola
doaj
Advanced Intelligent Discovery, EarlyView.We investigate MACE‐MP‐0 and M3GNet, two general‐purpose machine learning potentials, in materials discovery and find that both generally yield reliable predictions. At the same time, both potentials show a bias towards overstabilizing high energy metastable states. We deduce a metric to quantify when these potentials are safe to use.
Konstantin S. Jakob +2 more
wiley +1 more source
Advanced Intelligent Discovery, EarlyView.Phonons‐informed machine‐learning predictive models are propitious for reproducing thermal effects in computational materials science studies. Machine learning (ML) methods have become powerful tools for predicting material properties with near first‐principles accuracy and vastly reduced computational cost.
Pol Benítez +4 more
wiley +1 more source
Advances in the Semilocal Convergence of Newton’s Method with Real-World Applications [PDF]
Mathematics, 2019 The aim of this paper is to present a new semi-local convergence analysis for Newton’s method in a Banach space setting. The novelty of this paper is that by using more precise Lipschitz constants than in earlier studies and our new idea of restricted convergence domains, we extend the applicability of Newton’s method as follows: The convergence domain
Argyros, Ioannis K. +4 more
openaire +4 more sources
Advanced Intelligent Discovery, EarlyView.An explainable CatBoost model was trained to predict the bandgaps of 474 phosphate crystals based on composition and density descriptors. SHAP analysis identified two key variables—d‐electron‐count dispersion and atomic‐density dispersion—as the primary drivers of the model's predictions.
Wenhu Wang +3 more
wiley +1 more source
Order of Convergence and Dynamics of Newton–Gauss-Type Methods
Fractal and Fractional, 2023 On the basis of the new iterative technique designed by Zhongli Liu in 2016 with convergence orders of three and five, an extension to order six can be found in this paper. The study of high-convergence-order iterative methods under weak conditions is of
Ramya Sadananda +3 more
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Fortschritte der Physik, Volume 74, Issue 4, April 2026.Abstract String theory has strong implications for cosmology, implying the absence of a cosmological constant, ruling out single‐field slow‐roll inflation, and that black holes decay. The origins of these statements are elucidated within the string‐theoretical swampland programme.
Kay Lehnert
wiley +1 more source